Role of Dynamic Contrast-Enhanced Magnetic Resonance Imaging Parameters and Extracellular Volume Fraction as Predictors of Lung Cancer Subtypes and Lymph Node Status in Non-Small-Cell Lung Cancer Patients.

Abstract

Objective: The aim of this study is to determine whether dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)-based quantitative parameters and the extracellular volume fraction (ECV) can differentiate small-cell lung cancer (SCLC) from non-small-cell lung cancer (NSCLC), squamous-cell carcinoma (SCC) from adenocarcinoma (Adeno-Ca), and NSCLC with lymph node metastasis from NSCLC without lymph node metastasis. Materials and methods: We prospectively enrolled patients with lung cancer (41 Adeno-Ca, 29 SCC, and 23 SCLC) who underwent DCE-MRI and enhanced T1 mapping prior to histopathological confirmation. Quantitative parameters based on DCE-MRI and ECV based on T1 mapping were compared between SCLC and NSCLC patients, between SCC and Adeno-Ca patients, and between NSCLC patients with and without lymph node metastasis. The area under the receiver-operating characteristic curve (AUC) was used to evaluate the diagnostic performance of each parameter. Spearman rank correlation was used to clarify the associations between ECV and DCE-MRI-derived parameters. Results: Ktrans, Kep, Ve, and ECV all performed well in differentiating SCLC from NSCLC (AUC > 0.729). Ktrans showed the best performance in differentiating SCC from Adeno-Ca (AUC = 0.836). ECV could differentiate NSCLCs with and without lymph node metastases (AUC = 0.764). ECV showed a significant positive correlation with both Ktrans and Ve. Conclusions: Ktrans is the most promising imaging parameter to differentiate SCLC from NSCLC, and Adeno-Ca from SCC. ECV was helpful in detecting lymph node metastasis in NSCLC. These imaging parameters may help guide the selection of lung cancer treatment.